{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5d1e9d41",
   "metadata": {},
   "source": [
    "1.基于csv数据，影响可视化数据分布，计算各个维度对应的高斯分布概率密度函数\n",
    "2.建立模型，实现异常数据点检测\n",
    "3.可视化异常检测处理结果\n",
    "4.修改参数查看影响"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3cdb0eab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.046815</td>\n",
       "      <td>9.741152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.408520</td>\n",
       "      <td>8.763270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.195915</td>\n",
       "      <td>10.853181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9.914701</td>\n",
       "      <td>11.174260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.576700</td>\n",
       "      <td>9.042849</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         x1         x2\n",
       "0  8.046815   9.741152\n",
       "1  8.408520   8.763270\n",
       "2  9.195915  10.853181\n",
       "3  9.914701  11.174260\n",
       "4  8.576700   9.042849"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "data = pd.read_csv('anomaly_data.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6495ad69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可视化数据\n",
    "from matplotlib import pyplot as plt\n",
    "fig1 = plt.figure(figsize=(10,5))\n",
    "plt.scatter(data.loc[:,'x1'],data.loc[:,'x2'])\n",
    "plt.xlabel('x1')\n",
    "plt.ylabel('x2')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "78fd4a2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "x1 = data.loc[:,'x1']\n",
    "x2 = data.loc[:,'x2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f2b299a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = plt.figure(figsize=(20,5))\n",
    "plt.subplot(121)\n",
    "plt.hist(x1,bins = 100)#bins可以理解为将x轴分为多少份  hist是画直方图\n",
    "plt.xlabel('x1')\n",
    "plt.ylabel('counts')\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.hist(x2,bins = 100)#bins可以理解为将x轴分为多少份  hist是画直方图\n",
    "plt.xlabel('x2')\n",
    "plt.ylabel('counts')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "267ddfaa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.112225783931596 1.3559573758220915 9.997710507954398 1.30970711753864\n"
     ]
    }
   ],
   "source": [
    "# 计算均值和标准差\n",
    "x1_mean = x1.mean()\n",
    "x1_sigma = x1.std()\n",
    "x2_mean = x2.mean()\n",
    "x2_sigma = x2.std()\n",
    "print(x1_mean,x1_sigma,x2_mean,x2_sigma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "45d00a4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.59439512e-11 6.39250512e-11 8.87272428e-11 1.22853079e-10\n",
      " 1.69690787e-10 2.33815685e-10 3.21389865e-10 4.40690686e-10\n",
      " 6.02807607e-10 8.22558389e-10 1.11969027e-09 1.52045032e-09\n",
      " 2.05963243e-09 2.78323813e-09 3.75192518e-09 5.04546423e-09\n",
      " 6.76848160e-09 9.05783765e-09 1.20920788e-08 1.61035107e-08\n",
      " 2.13935729e-08 2.83523613e-08 3.74833421e-08 4.94345445e-08\n",
      " 6.50378126e-08 8.53580478e-08 1.11754798e-07 1.45959055e-07\n",
      " 1.90168713e-07 2.47166865e-07 3.20467940e-07 4.14497664e-07\n",
      " 5.34813972e-07 6.88377332e-07 8.83880464e-07 1.13214921e-06\n",
      " 1.44662831e-06 1.84396812e-06 2.34473095e-06 2.97423845e-06\n",
      " 3.76358483e-06 4.75084425e-06 5.98250452e-06 7.51516355e-06\n",
      " 9.41752964e-06 1.17727715e-05 1.46812688e-05 1.82638203e-05\n",
      " 2.26653703e-05 2.80593218e-05 3.46525087e-05 4.26909039e-05\n",
      " 5.24661477e-05 6.43229811e-05 7.86676738e-05 9.59775394e-05\n",
      " 1.16811627e-04 1.41822682e-04 1.71770457e-04 2.07536462e-04\n",
      " 2.50140207e-04 3.00757010e-04 3.60737401e-04 4.31628133e-04\n",
      " 5.15194803e-04 6.13446032e-04 7.28659126e-04 8.63407096e-04\n",
      " 1.02058687e-03 1.20344847e-03 1.41562486e-03 1.66116213e-03\n",
      " 1.94454957e-03 2.27074923e-03 2.64522422e-03 3.07396532e-03\n",
      " 3.56351504e-03 4.12098835e-03 4.75408930e-03 5.47112255e-03\n",
      " 6.28099878e-03 7.19323310e-03 8.21793529e-03 9.36579093e-03\n",
      " 1.06480323e-02 1.20763980e-02 1.36630808e-02 1.54206617e-02\n",
      " 1.73620317e-02 1.95002975e-02 2.18486742e-02 2.44203621e-02\n",
      " 2.72284091e-02 3.02855590e-02 3.36040854e-02 3.71956133e-02\n",
      " 4.10709290e-02 4.52397803e-02 4.97106689e-02 5.44906370e-02\n",
      " 5.95850519e-02 6.49973899e-02 7.07290248e-02 7.67790232e-02\n",
      " 8.31439500e-02 8.98176902e-02 9.67912882e-02 1.04052811e-01\n",
      " 1.11587236e-01 1.19376374e-01 1.27398820e-01 1.35629945e-01\n",
      " 1.44041928e-01 1.52603826e-01 1.61281695e-01 1.70038746e-01\n",
      " 1.78835554e-01 1.87630310e-01 1.96379110e-01 2.05036290e-01\n",
      " 2.13554802e-01 2.21886617e-01 2.29983157e-01 2.37795764e-01\n",
      " 2.45276170e-01 2.52376989e-01 2.59052217e-01 2.65257718e-01\n",
      " 2.70951715e-01 2.76095252e-01 2.80652639e-01 2.84591865e-01\n",
      " 2.87884969e-01 2.90508376e-01 2.92443171e-01 2.93675333e-01\n",
      " 2.94195898e-01 2.94001072e-01 2.93092277e-01 2.91476129e-01\n",
      " 2.89164364e-01 2.86173692e-01 2.82525597e-01 2.78246080e-01\n",
      " 2.73365350e-01 2.67917471e-01 2.61939965e-01 2.55473379e-01\n",
      " 2.48560834e-01 2.41247544e-01 2.33580328e-01 2.25607111e-01\n",
      " 2.17376436e-01 2.08936975e-01 2.00337061e-01 1.91624244e-01\n",
      " 1.82844865e-01 1.74043673e-01 1.65263471e-01 1.56544805e-01\n",
      " 1.47925691e-01 1.39441394e-01 1.31124239e-01 1.23003481e-01\n",
      " 1.15105211e-01 1.07452302e-01 1.00064406e-01 9.29579807e-02\n",
      " 8.61463532e-02 7.96398204e-02 7.34457728e-02 6.75688451e-02\n",
      " 6.20110873e-02 5.67721517e-02 5.18494939e-02 4.72385815e-02\n",
      " 4.29331083e-02 3.89252109e-02 3.52056831e-02 3.17641863e-02\n",
      " 2.85894535e-02 2.56694835e-02 2.29917255e-02 2.05432504e-02\n",
      " 1.83109093e-02 1.62814778e-02 1.44417855e-02 1.27788308e-02\n",
      " 1.12798807e-02 9.93255665e-03 8.72490595e-03 7.64545992e-03\n",
      " 6.68327969e-03 5.82799024e-03 5.06980380e-03 4.39953370e-03\n",
      " 3.80859948e-03 3.28902456e-03 2.83342739e-03 2.43500702e-03\n",
      " 2.08752414e-03 1.78527841e-03 1.52308296e-03 1.29623673e-03\n",
      " 1.10049544e-03 9.32041666e-04 7.87454678e-04 6.63680360e-04\n",
      " 5.58001701e-04 4.68010113e-04 3.91577845e-04 3.26831678e-04\n",
      " 2.72128066e-04 2.26029791e-04 1.87284222e-04 1.54803173e-04\n",
      " 1.27644376e-04 1.04994528e-04 8.61538736e-05 7.05222418e-05\n",
      " 5.75864847e-05 4.69092172e-05 3.81187773e-05 3.09003143e-05\n",
      " 2.49879133e-05 2.01576658e-05 1.62215986e-05 1.30223757e-05\n",
      " 1.04286946e-05 8.33130115e-06 6.63955354e-06 5.27847027e-06\n",
      " 4.18620451e-06 3.31189044e-06 2.61381376e-06 2.05786308e-06\n",
      " 1.61622370e-06 1.26627964e-06 9.89694001e-07 7.71641202e-07\n",
      " 6.00168280e-07 4.65665246e-07 3.60427378e-07 2.78294663e-07\n",
      " 2.14355752e-07 1.64705675e-07 1.26248185e-07 9.65350182e-08\n",
      " 7.36355916e-08 5.60317048e-08 4.25327096e-08 3.22073820e-08\n",
      " 2.43293752e-08 1.83336800e-08 1.37819762e-08 1.03351433e-08\n",
      " 7.73151616e-09 5.76973667e-09 4.29527006e-09 3.18983425e-09\n",
      " 2.36313709e-09 1.74643680e-09 1.28753781e-09 9.46913410e-10\n",
      " 6.94710241e-10 5.08440683e-10 3.71210322e-10 2.70360321e-10\n",
      " 1.96430545e-10 1.42369922e-10 1.02936793e-10 7.42448232e-11\n",
      " 5.34201225e-11 3.83430574e-11 2.74543875e-11 1.96101058e-11\n",
      " 1.39730519e-11 9.93220712e-12 7.04276862e-12 4.98177642e-12\n",
      " 3.51534702e-12 2.47454486e-12 1.73766326e-12 1.21724799e-12\n",
      " 8.50620155e-13 5.92973700e-13 4.12361730e-13 2.86064808e-13\n",
      " 1.97967396e-13 1.36667758e-13 9.41199362e-14 6.46606905e-14\n",
      " 4.43141283e-14 3.02961360e-14 2.06621462e-14 1.40574575e-14\n",
      " 9.54072297e-15 6.45950072e-15 4.36274445e-15 2.93943429e-15]\n"
     ]
    }
   ],
   "source": [
    "#计算高斯分布\n",
    "from scipy.stats import norm \n",
    "x1_range = np.linspace(0,20,300)\n",
    "x1_normal = norm.pdf(x1_range,x1_mean,x1_sigma)\n",
    "x2_range = np.linspace(0,20,300)\n",
    "x2_normal = norm.pdf(x2_range,x2_mean,x2_sigma)\n",
    "print(x1_normal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7b062a1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可视化\n",
    "fig2 = plt.figure(figsize = (10,5))\n",
    "plt.subplot(121)\n",
    "plt.plot(x1_range,x1_normal)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(x2_range,x2_normal)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94ee991b",
   "metadata": {},
   "source": [
    "上图是一个高斯概率密度函数图，到时候会给定一个值，求出来的函数小于这个值就是异常的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ee3cfeba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EllipticEnvelope()"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.covariance import EllipticEnvelope\n",
    "ad_model = EllipticEnvelope()\n",
    "ad_model.fit(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "dcb3e52f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1    276\n",
      "-1     31\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#预测\n",
    "y_predict = ad_model.predict(data)\n",
    "print(pd.value_counts(y_predict))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b6b37add",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4 = plt.figure(figsize = (20,10))\n",
    "plt.scatter(data.loc[:,'x1'],data.loc[:,'x2'],marker='x')\n",
    "plt.scatter(data.loc[:,'x1'][y_predict==-1],data.loc[:,'x2'][y_predict==-1],marker = 'o',facecolor='none',edgecolor='red',s=150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bf67997b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#修改参数看有什么影响\n",
    "ad_model = EllipticEnvelope(contamination=0.02)\n",
    "ad_model.fit(data)\n",
    "y_predict = ad_model.predict(data)\n",
    "fig5 = plt.figure(figsize = (20,10))\n",
    "plt.scatter(data.loc[:,'x1'],data.loc[:,'x2'],marker='x')\n",
    "plt.scatter(data.loc[:,'x1'][y_predict==-1],data.loc[:,'x2'][y_predict==-1],marker = 'o',facecolor='none',edgecolor='red',s=150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6935ccfb",
   "metadata": {},
   "source": [
    "修改小了contamination之后，异常值减少"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
